# Packages ----
library(tidyverse)

── Attaching packages ──────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.1.0     ✔ purrr   0.2.5
✔ tibble  1.4.2     ✔ dplyr   0.7.8
✔ tidyr   0.8.2     ✔ stringr 1.3.1
✔ readr   1.3.0     ✔ forcats 0.3.0
── Conflicts ─────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

library(plotly)

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

# Plot settings ----
theme_set(theme_bw())

# Knitr options ----
knitr::opts_chunk$set(message = FALSE, warning = FALSE)

catsvdogs <- read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2018-09-11/cats_vs_dogs.csv") %>% 
  select(-X1)

Missing column names filled in: 'X1' [1]Parsed with column specification:
cols(
  X1 = col_double(),
  state = col_character(),
  n_households = col_double(),
  percent_pet_households = col_double(),
  n_pet_households = col_double(),
  percent_dog_owners = col_double(),
  n_dog_households = col_double(),
  avg_dogs_per_household = col_double(),
  dog_population = col_double(),
  percent_cat_owners = col_double(),
  n_cat_households = col_double(),
  avg_cats_per_household = col_double(),
  cat_population = col_double()
)

names(catsvdogs)

 [1] "state"                  "n_households"           "percent_pet_households" "n_pet_households"      
 [5] "percent_dog_owners"     "n_dog_households"       "avg_dogs_per_household" "dog_population"        
 [9] "percent_cat_owners"     "n_cat_households"       "avg_cats_per_household" "cat_population"        

percent_owners_plot <- catsvdogs %>% 
  filter(state != "District of Columbia") %>% 
  ggplot(aes(x = percent_dog_owners, y = percent_cat_owners)) +
  geom_point(aes(col = state), show.legend = FALSE) +
  geom_smooth(se = FALSE, method = "lm")

ggplotly(percent_owners_plot)

college_majors <- read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2018-10-16/recent-grads.csv") %>% 
  janitor::clean_names(case = "snake")

Parsed with column specification:
cols(
  .default = col_double(),
  Major = col_character(),
  Major_category = col_character()
)
See spec(...) for full column specifications.

earnings_order <- college_majors %>% 
  select(major, median) %>% 
  arrange(desc(median))

earnings_order %>% 
  head() %>% 
  bind_rows(
    earnings_order %>% 
      tail()
  )

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